class_docstr: :class:`~opacus.optimizers.optimizer.DPOptimizer` compatible with
  distributed data processing
code: def step(
      self, closure: Optional[Callable[[], float]] = None
  ) -> Optional[torch.Tensor]:
      if self.pre_step():
          self.reduce_gradients()
          return self.original_optimizer.step(closure)
      else:
          return None
  
file_path: opacus/opacus/optimizers/ddpoptimizer.py
imports: from __future__ import annotations
  from typing import Callable, Optional
  import torch
  from torch.optim import Optimizer
  from .optimizer import DPOptimizer
label_desc: Use image node_id 4 for calling the DistributedDPOptimizer obj's underlying member method code with example usage: obj.step(closure) and returns: self, None